| Abstract |
Games are used extensively in modeling real life situations, where deep understanding and insights are required. Identifying the dynamics of real situations is considered the missing ring between the
theoritical games' studies and its application in real life. In this presentation, we reveal that it is possible to recognize and classify the type of interaction from a sequence of results without having any access to information about the players or the group themselves in strategy games, showing that different games' dynamics have consistent footprints along their evolutionary path regardless of the number of rounds within these games. These findings have a great impact on a wide range of fields from social networks, economics, politics to defence and security.
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